Introduction to Machine Learning 2

In this course we continue with discussing machine learning models and algorithms. While the focus in Introduction to Machine Learning 1 was on programming basic models yourself, in this course we will make more use of libraries for the elementary parts and the focus will mainly be on how to combine these parts into more

Plants and Micro Organisms

De cursus bestaat uit twee delen: planten en micro-organismen. In het plantendeel worden drie thema’s behandeld. Je bestudeert fotosynthesemechanismen (C3, C4, CAM), de invloed van interne en externe milieufactoren, en de rol van fotosynthese, ademhaling en morfologie in de koolstofbalans. Daarna verdiep je je in water- en nutriëntentransport (xyleem, floëem, transpiratie, wortelstructuur, rhizosfeer, exudaten, biotische

Bioinformatics, Data Analysis

De ontwikkeling van steeds nieuwe en betere high-throughput assay technologieën transformeert de moleculaire biologie in een razendsnel tempo. Sequencing van volledige genomen en de mogelijkheid om RNA, eiwitten, metabolieten en hun interacties op grote schaal (genoom-breed) te meten brengen een revolutie teweeg in biologisch onderzoek. Voor het eerst komen verschillende soorten data kwantitatief beschikbaar, en

Artificial Intelligence in (Bio-)Chemical Engineering

The digital transition of the (bio)-chemical industry and research requires new intelligent knowledge and decision-making tools. The increasing availability of data and computational resources over the past decade has led to a resurgence of machine learning-based research. Artificial intelligence has significant advantages over traditional modeling techniques, including flexibility, accuracy, and speed of execution. Therefore, artificial

Philosophy of AI (UvA)

In this course, we approach (the philosophy of) artificial intelligence (AI) from the perspective of theoretical philosophy. The course focuses on the discussion of the intelligence of artificial intelligence, in particular against the backdrop of the debate between nativists and empiricists. We will do so, following Cameron Buckner’s very recent book From Deep Learning to

Signal Processing

Digital signal processing is used in many modern computer sciences systems and applications. Examples are machine learning, artificial intelligence, and big data analysis; content recommenders in information systems; speech, music and image content based retrieval and searching; music and video compression; sensor data processing in embedded systems; bioinformatics and medical data analysis. This course deals

Principles of Plant Breeding

Online version of the course plant breeding. E-learnings. This course introduces students to key principles of plant breeding. Plant breeding is the science-driven creative process of changing the traits of plants in order to develop new plant varieties. Several essential approaches and tools used in the process are discussed: different modes of reproduction, selection methods,

Breeding for Abiotic Stress Tolerance

Abiotic stress is the stress imposed on plants by the non-living environment. Abiotic stress is responsible for huge yield losses in crops around the world. In this course we will assess the impact that abiotic stresses (like drought, salinity, nutrient deficiency, temperature) have on agricultural production, and provide you with knowledge and tools for successfully

Control Engineering

Besides a correct design or layout, good control systems are essential to guarantee that production systems operate and produce according the desired specifications. This course gives an introduction to classical control engineering approaches and discusses the standard methods and tools that are usually applied. The methods discussed in the course have a very wide application